As someone who uses statistics (and statistical methods) on a regular basis, I often find that the “headline figures” that get all the attention obscure as much as they reveal. For example, reporting a single benefit-cost ratio (BCR) for a project may conceal uncertainty about potential outcomes.
When talking about data, there’s a strong tendency to focus on the average value, without considering the variation in outcomes. So, for example, we get news articles like this:
Auckland house prices climbed to a fresh record last month, while the number of sales dropped from March’s peak, according to Barfoot & Thompson.
The average sale price rose to $804,282 in April, from March’s previous record $776,729, the city’s largest realtor said.
Averages are certainly useful, but it would also be helpful to know more about how the distribution of house values has changed. For example: perhaps the average is being dragged up by the sale of a small number of really expensive homes? It’s hard to know.
In fairness, the article does provide this data suggesting that there is a fair range of prices. But we don’t know whether the number of homes sold for under $500,000 is increasing, decreasing, or staying the same:
“157 homes sold during the month went for under $500,000, which represents one in seven of all homes sold. There is a good choice of homes in this price category but LVRs often mean potential buyers cannot meet the home deposit requirements.”
As an illustration of why we can’t rely solely upon measures of central tendency, such as the mean or median value, consider two hypothetical cities:
- City A has an average house price of $500,000, and a standard deviation in house prices of $50,000. (As a rule of thumb, if your data follows a normal distribution, 95% of values will be found within two standard deviations of the average. In other words, in city A, 95% of houses are sold for between $400,000 and $600,000.)
- City B, by contrast, has an average house price of $600,000 and a standard deviation in house prices of $150,000. (Implying that 95% of houses are sold for between $300,000 and $900,000.)
I’ve graphed the distribution of house prices in these two cities below. City A is in blue, while city B is in red.
We can immediately see two things. First, the average house in A – found at the peak of the bell curve – is cheaper than the average house in B.
A second key fact, however, is that B actually offers more affordable houses overall, in spite of its higher average prices. This can be seen pretty easily on the chart – B has a much fatter “tail” of low-priced houses than A does.
Let’s think about what these two cities offer for households on lower incomes. Consider what house-hunting looks like for a household earning $50,000 a year.
If these people were basing their decisions on where to live on average house prices alone, they’d clearly prefer to live in city A, where average prices are $100,000 lower. But once they got there, they’d have a lot of trouble finding a home that they could afford.
Because city A has such little variation in house prices, it’s hard to find any houses that sell for less than $400,000. Assuming a 10% down-payment and a 6% mortgage rate, our household would have to pay $26,000 in mortgage repayments every year for the cheapest house on the market. Over 50% of their annual income!
By contrast, if they’d looked behind the headline figures on average house prices, they would find that city B offers many more affordable homes. Around 5% of homes in city B sell for less than $350,000, and it’s possible to find homes for $300,000 or less.
Under the same mortgage assumptions, our household would have to pay around $19-22,000 in mortgage repayments every year to live in a cheaper house in city B. This still isn’t great – it’s around 40% of household income – but it’s better.
In other words, although the first city seems more affordable based on its average house prices, it is actually likely to be considerably less affordable for many of the real human beings that are trying to live in it.
How do you think we should measure and report on house prices?
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Easiest measure for investors I know has always been Trademe. For years they simply put in bracketed prices for a particular area and then readily graphed the volumes of properties available (simple number of listings). Not a perfect science, but a reasonable ball-park indicator. Trademe these days provides those stats so it is no longer necessary to create the graphs manually. Obviously there will be subtle aberrations, especially in the current sellers market (Auckland) where fewer houses get listed and some brackets are more readily offered for sale than the normal spread across all brackets.
I love doing RE site searches for cities around the world. There are several things that Demographia understates. One is that the price of space per square foot is much higher for more expensive cities – the houses are usually very much smaller, sections smaller still, and stacking upwards only increases the price of sites exponentially.
Another thing Demographia understates, is the impact at the bottom end of the market. Median multiple 3 cities tend to have an amazing even spread of house prices – even $90,000 houses (townhouses, dilapidated old cottages, etc) for $30,000 income earners. But cities with median multiples of 6 and higher definitely do not have $180,000 homes for the $30,000 income earner – the bottom end of the market is distorted upwards.
There is actually a paper that confirms this phenomenon in UK cities: Matthew Keep (2012) “Regional house prices: affordability and income ratios”
The bottom quartile multiple is significantly higher than the median multiple in UK cities.
So yes, I agree that Demographia has its faults, but it understates the problem in the unaffordable cities, it does NOT overstate the problem!!!
This sort of theory is all well and good, but is there any reason to believe this sort of variation actually exists between cities. It might be that any agglomoration of hundreds of thousands of homes rapidly reaches a fairly uniform standard deviation in prices. It would be nice to see with some real data from cities around New Zealand.
I’m intending to do a follow-up post on how the distribution of rents varies over space and time – MBIE publishes some quite good data on weekly rents for new tenancies. They’ve just reported some of it in a slightly obscure form, so some maths are required to obtain something that would make sense to the average reader.
Excellent.
This is absolutely correct.
Auckland doesn’t necessarily have a housing shortage problem it has a housing product shortage.
Where are the small two bed homes (entry level homes). We failed to build them in the past and continue not to build them in a reasonable quantity. and we are paying the price for it. So now we are left with you have to have a million dollars to buy anything anywhere, large or small, standalone detached or apartment. Look out for when the bubble will burst because demand is only facilitated by easy and cheap financing.
http://www.stats.govt.nz/browse_for_stats/people_and_communities/housing/auckland-housing-1991-2013.aspx – page 87 provides the evidence for this
Surely an economist should use “mean” instead of “average” to avoid confusion here? Or even “arithmetical mean”
Unless “average” is actually “median”? Would help to know which!!
I used “average” in place of “mean” to attempt to avoid confusing people who are less familiar with statistical terms.
Medians are usually the preferred way of reporting house prices, and REINZ and CoreLogic (QV) tend to focus on those. In the link above, though, Barfoots are using means/ averages instead.
NZ Herald, to its credit, will report both median and mean prices for a given period, and if it doesn’t it only ever reports the median. Shame they aren’t as diligent about reporting on incomes.
How about: How many km’s do you need to look from the city to buy a 2 bdr house / town house / terraced house for say 5x median income? This is where I think Auckland is especially bad – you will probably be looking at least 15km out, that may be worse than London or New York!
Nah, you can get that inside 10km. Median household income in Auckland is $76,500 according to the Census, which gives us a figure for your benchmark of $382k. There are 2br town houses available around that price within the old Auckland City, though their number is fast reducing.
I’d be surprised, unless you are talking about something with overhead transmission lines / on a main highway / next to a gang pad / etc.
I live about 10km away from the city in southern Mt Roskill and a small house on a 400m2 section under transmission lines went for 612k, granny flats going for more than 400k, 1950’s 3bdr houses are around $900k. We’re talking about some pretty average houses in a pretty average area with the only real advantage being ‘only’ 10km from the city.
Median household income is $68,600. I’d be very surprised if you could find a 2 bedroom place anywhere in the urban area that isn;t a leaky building for $343,000
I saw a unit in Otahuhu near the train station going for about that much the other day.
Was in habitable though?
I agree, Jimbo, that would be another excellent idea. Housing options and price levels at given distances from the city centre. Actually London is very bad, nothing is affordable regardless of how tight it is. New York has a good chance of being better than Auckland, though! It really all comes down to the cost of land per square foot, and the level this rises to as allowed density is increased. There is such a thing as a city where site values are pretty static regardless of what density you are allowed to build – these cities happen to be the ones with a free-sprawling fringe.
Here is what you get inside the ring-road in Houston, in townhouses for $140,000 or less:
http://www.realtor.com/realestateandhomes-search/Houston_TX/type-condo-townhome-row-home-co-op/price-54000-140000/sby-2?pgsz=50
We are talking about a city whose CBD has more Fortune 500 Head Offices than any city outside New York. Lest people think Auckland is something special!
I was interested to see where the properties from that search were in Houston.
Only one, a one bedroom unit, was within 8kms of central Houston. All the stand alone houses were 20-30 miles (so 32-48 kms) from central Houston.
So that means you are talking about the equivalent in Auckland of houses in Drury out to Pukekohe and even further out.
Now I accept that you would struggle to get a house for less than $400,000 in those areas of Auckland and I am not disputing that housing in Houston is cheaper. But I also see the trade off there in terms of auto dependent living and the associated travel costs, plus loss of quality of life.
And I still have not seen you yet acknowledge in any of your comments referring to anywhere that doesn’t speak English. Again, an incredibly narrow focus to your evidence. One that is also adopted by Demographia.
Headlines are about selling news, not providing information. Lobbyists like Demographia are about pushing a preconceived notion. Measuring affordability correctly might not be their priority.
Comparing average house price month by month in isolation is not useful at all, except to a news organisation who is looking for a headline and a real estate company who is hoping for some free (or paid for?) publicity.
Using averages to search for trends over significant periods of time is a quick and easy option.
Using averages to compare two datasets does not work well (as highlighted by your normal curves) without also looking at standard deviation, interquartile range and median as a package.
I like box and whisker graphs.
I think I mentioned it last time you posted, but averages are…. tricky. What would, I think, be useful, would be to plot house prices against wages/salaries. If the bank’s recommended mortgage ratios are taken, of 3 to 3.5 times your salary to size up your mortgage, then that should be plottable. A young graduate on say, $50,000 could therefore get a mortgage of $150,000 but there are no houses in that range. A salary of $100,000 is actually (and sadly) in the top echelon of earnings in the country (top 10%?) and could only get you a mortgage of $300,000 – and yet the average price of a house in Auckland is now around $750,000?
Clearly, the “average” salary of Aucklanders is not $250,000 per year – or at least I hope it is not, as it is certainly not that down here in Wellington. Indeed, the figures for the last 2014 quarter available indicate that nationally, median wages are $31,200 annually, and average wages & salaries are $51,532. Clearly, also, the figures are blurred by the massive amount of deposit people are able to put down, either by selling their existing Auckland house, or by bringing massive amounts of cash in from overseas. Incidentally, London house prices are grossly inflated too, and arguably inflated there at the top end by Russians bringing in ill-gotten gains for money laundering.
But back to Peter’s graphs – nonwithstanding the difficulty of getting info on deposit size, a graph of salary vs house price would be useful…
Right, what makes affordability discussions difficult is not just the distribution of house prices (for which public data is pretty readily avaiable) but also the income and wealth distribution. Usual quoted figures (median ratios etc) obfuscate the interplay between these two things. City A in the graph could well be more affordable than city B for the local population.
That is an important point. Actually, median multiple 3 cities tend to have an amazing spread of house prices matching income distribution – even $90,000 houses (townhouses, dilapidated old cottages, etc) for $30,000 income earners. But cities with median multiples of 6 and higher definitely do not have $180,000 homes for the $30,000 income earner – the bottom end of the market is distorted upwards.
There is actually a paper that confirms this phenomenon in UK cities: Matthew Keep (2012) “Regional house prices: affordability and income ratios”
The bottom quartile multiple is significantly higher than the median multiple in UK cities.
I agree that Demographia has its faults, and Wendell Cox is aware of my opinions; but my opinions are that Demographia understates the problem in the unaffordable cities, it does NOT overstate the problem!!! The other significant point that Demographia does not expose, is that the price of space per square foot is much higher for more expensive cities – the houses are usually very much smaller, sections smaller still, and stacking upwards only increases the price of sites exponentially.
Interesting link and assertions Phil. Can I just check a couple of factoids with you, from the Keep study and the Demographia report? The Keep report is of course a Parliamentary report…not sure if that gives it credibility or not, but you seem happy to quote it so I will follow suit for now;
– Demographia, London median house price to median income, 2014, p12 – ratio of 8.5.
– Keep: average house price to income ratio, London, 2010 (last date in report), p8 – ratio of 4.7.
There is of course 4 years of growth in between these dates, but as Keep reports that it took 15 years to get from a ratio of 3.0 to 4.7, one has to wonder – what makes you think Demographia is under-reporting….?
Averages eh? A man with his head in the oven and feet in the fridge, on average is a comfortable temperature.
Anyone worked out yet how Ricardo gets in first all the time? Is he a bot?
Not a bot. Just get up early in the morning. Lots to do each day.
Good post Peter – at the risk of possibly preempting what you might write about in the future, I’ve gone and looked up the number of listings in each TradeMe price bracket: https://drive.google.com/file/d/0Bw4OPC2S9xTrNWcwcEFrYjZEd0E/view?usp=sharing
A lot of overlap there, since you get 12,989 listings when doing it that way, whereas you only get 6,524 when you search under “any price”. But still interesting.
Auckland doesn’t seem to come off well on this data – there’s a long tail of more expensive properties, which you’d expect, but there’s very little under say $500,000. So we’re more like a long-tailed City A.
Of course, this analysis also misses things like minor dwellings, which can’t be sold separately so don’t show up in the data. But they would often constitute affordable rentals.
A long tail at the upper end, and a short tail at the lower end, is indeed a short tale: no affordable housing.
That is an excellent observation; it is what I have been saying often in these arguments. Median multiples rising as cities land costs inflate is only one part of the problem – the entire distribution of house prices is distorted in the direction of no tail at the low end. In fact, an opinion piece authored by me, printed in the Sunday Star Times Business section 7 Sept 2014, said:
“…there is cause to complain about the median multiple as an affordability measure.
When urban land costs inflate, while the median multiple house price may rise to “only” 7+ (from 3 as recently as the 1990’s), the house price distribution is changed considerably, the bottom of the market being eliminated completely. A “bottom quintile multiple” would have inflated far more than the median multiple, and would be a far more damning statistic, especially as we claim to care about poorer people.
The actual match-up of homes with purchasers across the income spectrum, is skewed completely, so that the people in the bottom quintile do not get to buy at all. Eventually, increasing numbers of Kiwis with go into retirement as lifelong renters with no home of their own free of encumbrances and ongoing charges.”
If you do a search on TradeMe it will return a fair amount of properties which have an asking price slightly higher than your maximum.
The main problem however is that the majority of properties are sold by auction so you can’t really put a price on those properties. Some of the results will be for properties sold by auction with a valuation quite a bit larger than your upper price limit.
Note also that the lower brackets are very narrow. If you indeed plotted the amount of properties in the bin on the Y axis, this will make the lower end of the graph appear lower than it should be in a histogram.
Great work John! Thanks for putting some data to the hypothesis. This does not look like a pretty picture.
At a quick glance, it doesn’t look like the data is not normally distributed. But perhaps we shouldn’t expect prices to be normally distributed, given that they have a minimum value of zero. Does log(price) follow a normal distribution?
Not just a minimum value of zero – you would also have to consider things like minimum lot sizes, legacy infrastructure etc which are going to impose limits on how low house prices can go. Anyway, I think you’d always get a lopsided distribution with a long tail of more expensive properties, at least in cities where wealthier people want to invest in property. But it’s disappointing that there aren’t more properties at the cheap end.
Whatever happened to the REINZ stratified index…? One has to wonder whether it appears to have been killed off….
https://www.reinz.co.nz/reinz/index.cfm?68A16290-F7FA-4733-D803-99EAF31D12E5
http://www.rbnz.govt.nz/news/2009/3706847.html
REINZ have a page at https://www.reinz.co.nz/reinz/public/reinz-statistics/reinz-statistics_home.cfm, and I’m fairly sure the “Housing Price Index” graphs are actually the stratified ones.
You are right Peter. The average doesn’t reflect the lower end of the market. But if you base affordability on the lowest decile say then you can’t compare that to the average wage, you should also use the lowest decile of wages. The averages are simply a snapshot in one number that have some meaning to people.
Incidentally, if we take a reverse engineering approach to get to the same answer…. If (as reported in the original post) the reported Average price in Akl is now $804,282 and we assume a 20% deposit, then the Average Auckland buyer would have had to get a mortgage of $643,000. Assuming it is a power-hungry couple, then the bank would take one full salary and half the second salary as potential household earnings? With a mortgage 3 x their earnings, each of them would have to be earning $143,830 pa, which is 2.5 to 3 x the average salary. Each. So, that suggests to me that not only are this couple screwed (they are earning up to 3 x the average salary, and yet can only afford a very average house), but also that the average salary earner is even more totally screwed (but we already knew that) being well away from ever reaching the level of affordability. People earning below the average (which of course is 50% of the population – or more likely, more) are just totally, totally screwed forever. How pleasant to know that.
Seems to me, that the only, and the most responsible thing to do, would be for the Government to carefully engineer a drop in prices, rather than wait for the market to crash and suffer a catastrophic crash in prices. They could do this by building housing themselves, and releasing it only to the lower end of the market, at prices far below the current market rates – this would have the effect of pulling market prices down. By how much, depends on how many houses they build. There would have to be caveats – such as don’t allow people to on-sell the houses for a decent period of time – or the Gov could rent them out, at a price (below market rate) of their choosing. Ironically, this would be just like a State housing program… and of course, the present government is doing the complete opposite, ie selling off state housing, and thus making the whole matter worse, not better.
Guy there won’t be crash. Maybe a levelling at some stage. 700k mortgages are common and repayments around 1000 a week. My daughterand partner recent got one and they don’t earn anything like 140k each. Banks don’t care so long as sizable deposit. Banks will always get their money back if it goes bad.
Yeah, highly leveraged property out of whack with earning power has never caused issues anywhere else, so why would it in NZ? We are so far away anyway.
Ricardo, famous last words “there won’t be a crash” – The Koreans didn’t think there would be a crash in 1995. The Irish didn’t think there would be a crash in 2001. The Americans didn’t think there would be a crash in 1931, 1973, 2001, 2007 etc. NZ has had them before. What makes you think that you / us / we wil be any different, especially as we have less control over our finances and exchange rate than most countries?
We have no way of knowing when and where there will be a crash. I’ve lived through 2 or 3 already, and people always said that there wouldn’t be a crash, shortly before there then was one… Actually, we need a property price reversal – a gradual let down would be preferable to a crash, but if you don’t have one by choice, then you have the other served on you by the laws of supply and demand. 700k mortgages are only serviceable when the bank says they are – as soon as they withdraw their support (and they have in the past, and they will again in the future, because they can) then the 700k mortgages are suddenly not at all serviceable. ….and, phut.
Guy: you and DavidJRoos are onto it. I would bank on an absolute bloodbath of a crash in around 2023 if it has not come before then. I recommend the cycle-length theories of Phillip J. Anderson to help explain why on earth countries like NZ, Australia and Canada managed to dodge the crash they should have had at the same time as those other countries that all went around 2007-2008. Our prices were already high enough by then. The highest median multiple in Ireland was Dublin at 6.0 in 2007 – Auckland was higher than this even back then.
But once your government and central bank has managed to avert a crash by means that the crashed nations did not have enough forewarning to use, the next time does not come round for a long time, until a whole economic cycle has passed – it is not a question of putting it off just a few years. But when it comes, it will not be stoppable by the means that stopped it in 2008 onwards. Or any other means. The proviso to this “late crash” theory is that other large nations with a completely different cycle timing – like China – tend to pull smaller trading partners cycles into their orbit. Hugh Pavletich may be right about a China crash pulling us down sooner rather than later.
” Banks will always get their money back if it goes bad.”
Considering they don’t lend any of “their” money out in the first place. Remember, when you get a mortgage you are not “borrowing” money off the bank. You are creating completely new money out of thin air by way of your signature on the mortgage papers. The bank gets to charge you interest on this bank credit and in the end the bank ends up with 2 houses worth of interest whilst you end up with one house. The bank has zero risk coming to the table with nothing at all, doing nothing at all and taking the most rewards.
The trouble with State housing, or subsidies, in a housing market distorted by land supply issues, is that there will always be social injustice lumbered onto some segment of the population – those who rank just higher on the socio-economic spectrum, than the level to qualify for the subsidy or the State housing. This point is powerfully made re the UK, by James Bartholemew in his new book “The Welfare of Nations”. By 1974, 1/3 of the British were in Social housing and the next 10% or so of the population who were not, were worse off than those who were. This is an unresolvable problem by that approach. Making housing affordable by removing land owners powers of extraction of economic rent, is the answer. You literally barely need social housing at all in any median multiple 3 city. The tail of housing unit prices at the low end is so long, and the same applies to rents, there is something affordable to literally anyone. Interestingly nearly 50% of people in Houston do rent, there is not the same pressure, pressure, pressure to get on the home ownership ladder before it is pulled up any further out of reach. And the rents are as ridiculously affordable as the prices to buy are.
Guy. 50% of people earn less than the median income, not the average. In fact, in NZ it is closer to 70% of the population who earn less than the average income. Which is a classic example of why using the average in reports is completely meaningless and is in fact quite misleading to most people who mistakenly think that the average is around the 50% mark which it never is. The median should always be used, that way you know that 50% are higher and 50% are lower.
Gareth Morgan advocates for a period of stagnation, rather than a crash. Others may argue that a short, sharp shock is better than a long protracted period of nothing happening.
I’m not making a prediction but what has happened before in Auckland’s real estate boom-bust history [ie all of it], is quick feverish booms followed by long periods of flat-lining. However in the down phase a shake-out does occur, with good properties holding their value and poor ones slipping back. And note that that good and bad means in terms of both location and the state of the buildings.
And in terms of locational value we have had two major shifts along side these rhythms [broadly speaking]: 1. Second half of last century older inner city areas lost their value over new outer areas, and then 2. Those same properties regained their value this century. As the value of proximity to the centre was rediscovered, most dwellings were completely rebuilt so they now have both strong locational and inherent value, after previously being both rundown and in unfashionable places.
Therefore I really don’t expect the inner suburb market to correct much at all at this boom’s close. The only way to make living in these areas more affordable is to add as much new stock as possible to THIS market, ie more cheaper inner located dwellings. This can only be done by going up; apartments. Additionally adding say 10k apartments to the city and city fringe would also not adversely affect the existing housing stocks value as they’ll still have their size and detached point of difference. And would add so much to the vitality and options socially, and commercially that I suspect in fact the reverse would occur.
My guess then is this is not a bubble in city proximate locations.
There are NO cities that build predominantly denser housing, where this housing is cheaper than any Demographia Median multiple 3 city.
All Demographia Median multiple 3 cities are low or at most medium density.
My complaint with Demographia is that it UNDERSTATES the full extent of the problem, because all denser cities not only have median multiples of 6+ but the cost of living space per square foot is many times higher. You pay double, for a lot LESS space.
The cause is ALWAYS an absence of rural land able to be converted competitively to urban use, which results in all site rents being derived by “differentials” relative to that rural land. When the total supply of land is rationed by planning or some regulatory mechanism, site rents/values are derived from a process called “monopolistic competition” – basically everyone has to pay “the maximum they can stand” rather than “what developers competing with each other can convert the raw materials to finished product for and make a modest profit”.
Saying that building denser on a smaller, rationed amount of land will result in cheaper housing, is like saying that rationing the food supply so people won’t over-consume food, will result in people spending less on food “because the quantity they consume will be smaller”. Rubbish. What happens is liferaft-ethics bidding wars for the available supply, and people bidding more and more per unit of product the further the supply is reduced. To overcome this you need to suspend markets altogether, go full Commie, and we all know how well that works.
Basic math, Phil. The land cost per unit in a multi-unit structure is clearly lower, what ever that cost is, especially if there are a great many units. And they ain’t making no more land in Ponsonby.
And the price spread shows that that’s the kind of place where lots of people want to live in Auckland. Why should you be allowed to force them out of town just cos you think driving and sprawling is better, or even comparable. If you wish to be considered anything other than a crank you cannot, as you constantly try to do, compare a dwelling half way to Hamilton with one on Queen St. That is not apples with apples.
Sure something 60km out may be cheaper but so what; coal is cheaper than diamonds; they’re both just carbon, right? It is clear you don’t understand that location is the one defining and immovable characteristic of dwellings, but it is.
‘building denser on a smaller, rationed amount of land will result in cheaper housing’. Yes. It will result in cheaper housing options IN THAT AREA. You generalise everything out to meaninglessness. I can already find cheap accommodation in Te Kuiti; but that is irrelevant to my desire to live somewhere proximate in Auckland.
You are not on planet earth with your obsessive rantings.
I am very much on planet earth, that is where I am observing the evidence.
This is the crux of the problem – yes, if you buy a site for X dollars, the cost of land per unit will be lower if you build more units.
But you are taking the price of a site as a given. Urban land markets derive the price of sites in ways that differ according to the type of land market it is. If what you were saying was true at the level of “city versus city”, Hong Kong would be affordable – significantly more affordable than Houston. The fact that it is not shows that it is you that needs to be willing to learn more about realities on planet earth.
Sites in cities with freedom of fringe growth, are indeed anchored at a “given” site value. I have explained this numerous times. But site values in cities without the ability to convert rural land to urban use, are elastic to allowed density. Again, I am merely observing the reality in the broad evidence from cities all over the world. Turning Auckland into a land-rationed city will make its sites, too, inflate in price faster than the trade-off of density “should” be lowering the cost of housing according to your assumption. Your assumption never actually applies in real life, in any city anywhere. The onus is on you, and Peter Nunns, to point me to a single city where density is high, site values are low and flat and equivalent to affordable cities, and there is a saving in cost of land per housing unit. There ain’t no such evidence.
Houston and Hong Kong are apparently the only cities that exist on the planet earth. Please expand the cities you look at for evidence.
There are many European cities that achieve low multiples with dense housing. Why don’t you look at those cities?
Basic maths Patrick is not comparing an apartment with a larger dwelling and saying it is affordable, just because the price is relatively lower, if you do that you are on the slippery slope to saying a shoe box in the middle of the road is more affordable than an apartment.
But there is a correlation in price between the CBD and the fringe, irrespective of whether the city has restrictive or less restrictive zoning, and that the price is set from the fringe inwards, not the CDB outwards.
The arithmetic could be comparing an apartment of same size, at same relative location in a city with restrictive zoning against one in a city with less restrictive zoning.
Whatever the land cost that is pro-rated in a multi-unit development it is still costing far more than it should in Auckland, and as little as you may think the cost of land is, the cost of construction and fees far offsets any saving in land.
I don’t care whether people want an apartment in the CBD, or a house in the suburbs. Build up, down and out.
But what I care about is the amount of wasted non-valued costs that people pay for no extra amenity, especially when it means hard earnt money is diverted to pay for a needless cost when it is needed for education and health to name a few.
And as far as location goes, the number one location price determinant is a private long view shaft.
Affordable doesn’t mean good value, it doesn’t mean a sweet deal, it doesn’t mean bang for buck. It means something you can afford.
My $10 jandals are extremely affordable. Perhaps not as good value as a $250 pair of indestructible hiking boots that would give excellent foot protection and last forever… But they are very affordable and sometimes you only need something basic under your feet.
But why pay $10 when you could have purchased them for $5?
DAS I found your shoe box for sale in a Vancouver art gallery! For a mere $50 you can get on the property ladder by buying a cubic foot of space…..
http://221a.ca/cube-living
Also worth reading is
http://ounodesign.com/2013/02/17/everybody-works-but-the-vacant-lot/
That’s so affordable, even the residents of East Hastings St can afford that, can they?. And of course, Vancouver is a city that Auckland wants to emulate. It certainly is going is the right direction, but until they get their own equivalent of East Hastings St https://www.youtube.com/watch?v=wwJkqTZ5H_s , they can’t really say they have made it.
Hi Phil
Last week, you asked why I hadn’t responded to your comments. Your comment here sort of illustrates the reason why. While I don’t disagree with all of the points you’re making, they’re pretty off topic. This post is arguing that it’s necessary to have information on the _distribution_ of house prices in order to properly understand differences in housing affordability. Rather than commenting on that idea, you’ve posted a monologue on greenfield land supply.
I’ve noticed that rather than engaging with and considering others’ points of view, your comments _always_ return to making that same point. While we like to see active discussions with different points of view represented, it sometimes feels like you’re here to shout at other commenters rather than converse.
Look, you obviously read widely on transport and urban issues and have perspectives to add the conversation. But if you want to do that _effectively_, you really have to reconsider your approach to writing comments. Less is often more.
Peter, thank you for asking for clarification. I am addressing your assumption that your city with a substantial amount of lower-cost housing, has this because it allows denser housing in some locations. I agree that this is true if the city’s site values are generally low and do not rise with allowed density. But this is only the case if the city has freedom of fringe growth. It is certainly true in median-multiple 3 cities. But the cost of land is so low in such cities, that it is never true that they have a greater spread of house prices on the HIGH side than any city with a constrained fringe, and high allowed densities. In fact using your graph, I would say that if City A was Hong Kong, it would need the curve to be shifted a long way to the right, and if City B was Houston, it would need the curve to be shifted a long way to the left. Does that clarify my point and relate it directly to the point you are trying to make? I have already noted from the evidence on filtered searching of RE sites, that median multiple 3 cities have far more lower cost housing available – there is simply no such thing as a median multiple 6 city, or any dense city, with housing like THIS:
http://www.realtor.com/realestateandhomes-search/Raleigh_NC/beds-1/price-26000-160000/sby-2?pgsz=50
http://www.realtor.com/realestateandhomes-search/Philadelphia_PA/beds-1/price-30000-150000/sby-2?pgsz=50
http://www.realtor.com/realestateandhomes-search/Houston_TX/beds-1/price-30000-130000/sby-2?pgsz=50
Phil – one more time – I haven’t seen anyone arguing against freeing up fringe land. Stop creating a strawman that anyone is arguing against that.
But I personally am looking for balance in freeing up land. Freeing up the ability to build up and out. Then people can have real choice and the market can respond.
Plus charging the real cost of that expansion. Not transferring the transport cost of outward expansion to the inner areas where the outer suburbanites want to drive through to their destinations.
condescending response Peter. Isn’t the whole post actually off topic, seen as its supposed to be a transport blog and all?. its becoming hard reading all these posts, you should set up a housing economics blog. Just sayin…
Its there blog, they can write about whatever they like. If you don’t like it, get your intelligent, evidence based debate elsewhere.
And good luck finding it.
I’ve just received a response on Twitter from Stephen Jones of the UK Sunday Times. Draw your own conclusion.
https://twitter.com/stephenjones9_/status/608225141777137664
Fake identity of a certain troll who owns a house under a certain bridge.